There are more songs inspired by classical pieces than you might think…

Portfolio for the course Computational Musicology


Some time ago I heard a song named ‘a Fifth of Beethoven’ by Walter Murphy,
and I really liked it. It is a disco instrumental song based on Beethoven’s Symphony No. 5.
I thought using famous classical music pieces to create new songs of another genre is a really cool concept. So I did some research and discovered that there are many more famous songs that are based
and inspired on a classical piece of music, also songs I know for a long time
but never knew that they have a classical origin.
My corpus includes classical pieces and their linked new songs.
I have found 25 pairs, so 50 songs in total.
I think that this corpus makes really interesting comparisments possible, on different levels.
For example between the songs based on the classical songs.
What are the differences and similarities between these songs?
Is the classical input used in the same way? Is there an common genre?
But of course exploring relation between the song based on a classic song and the original classical song itself is really interesting.
To what extent do you see the original classical back in the new songs? In which way is the original song adapted in de new song? Which changes are made? Maybe the tempo changed or other instruments are used.
There are pairs of tracks in the corpus, like ‘I can’ – Nas/‘Für Elise’ -Beethoven and ‘A fifth of Beethoven’-Woody/ Beethoven’s Fifth Symphony- Beethoven,
in which the relation with the origin classical song is very obvious. But there are also pairs in the corpus in which the original songs are more subtly included, like ‘Grace Kelly’- Mika / ‘Largo Al Factotum’- Rossini.
It’s important that I define my research a bit more, but I think this is a really interesting and fun corpus to explore with enough possibilities.


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songs in the corpus

New
I can - Nas Fur Elise - Beethoven
A fifth of Beethoven - Walter Murphy Symphony No, 5 in C minor - Beethoven
Because - The Beatles Sonata No. 14 “Moonlight” in C sharp
Can’t Help falling in Love - Elvis Presley Martini: Plaisir d’amour - Jean-Paul-Egide Martini
All by myself - Eric Carmen Piano Concerto No. 2 in C minor - Sergei Rachmaninoff
The Globalist - Muse Nimord From Enigma Variations - Edward Elgar
Say You’ll Go Clair de Lune, L.32 - Claude Debussy
Old money - Lana Del Rey A time for Us - Nino Rota, Angele Dubeau
Little Me - Little Mix Pavane, Op. 50 - Gabriel Faure
I Believe in Father Christmas - Greg Lake Prokofiev: suite from lieutenant kijé - Sergei Prokofiev
Road to Joy - Bright Eyes Symphony No. 9 in D Minor, Op. 125 - Ludwig van Beethoven
It’s A Hard Life - Queen Vesti la giubba - Ruggero Leoncavallo
Tocacata - Sky Toccata and Fugue in D minor - Johann Sebastian Bach
A Whiter Shade of Pale - Procol Harum Air on a G string - Johann Sebastian
Could it Be Magic - Barry Manilow Preludes, Op. 28: No 20 in C minor - Frederic Chopin
Go West - Pet Shop Boys Canon in D - Johann Pachelbel
Alejandro - Lady Gaga Csardas - Vittorio Monti
Ave Maria - Beyonce Schubert: Ave Maria, D. 839 - Franz Schubert
Sara - Starship Fantasia on a Theme by Thomas Tallis - Ralph Vaughan Williams
Grace Kelly - MIKA Largo al factotum - Gioachino Rossini
Exit Music (For a Film) - Radiohead Prelude in E minor, Op. 28, No. 4 - Frederic Chopin
Bad Romance - Lady Gaga The Well-Tempered Clavier: Book 1 - Johann Sebastian Bach
Russians - Sting Lieutenant Kijé, Opt. 60: 2. Romance - Sergei Prokofiev
My Reverie - Ella Fitzgerald Reverie - Claude Debussy
Hey Jude - The Beatles Arioso (Adagio in G) - Johann Sebatian Bach

How do the inspired newer songs relate to the classical songs?


A first look on the spotify API features of the two playlists

In this graph you can have a look at the different features of the inspired songs and the features of the original songs. The lines in the plot show if there is a decrease or increase in value of the different features. A yellow-ish line means that from the inspired newer song to the original classical song, there is an increase of the feature. A blue-ish line means that from inspired newer song to the original classical song, there is an decrease of the feature.

difference of the features (highest differences on top) inspired newer songs

original classical songs - instrumentalness:0.527 - acousticness: 0.521 - energy: -0.428 - valence: -0.210 - danceability: -0.170 - speechiness: 0.129 - liveness: -0.039

Inspired but apparently with a lot more energy and loudness


Some more interesting features

This plot shows 4 variables. The x-axis variance, the y-axis energy, the size of the dots is loudness and the color is the mode.It points out some difference between the classical songs and the newer songs. It’s interesting to see that the the values of the features of the classical songs are more clustered, while the ones of newer songs are more spread out. A possible explanation could be the fact that the original classical songs all are all in the same genre; classical music. The playlist of the inspired newer songs, on the other hand, contains more genres, like pop, hiphop and jazz.

Because of the different scale, loudness isn’t showed in the overview graph on the previous page, but it’s an interesting feature, so I used a different graph to show this. The histogram of the loudness feature shows a clear distinction in values between the two playlists. The newer songs are a lot louder.

Compairing two songs with two self-similarity matrices


The self-similarity matrices are an interesting tool for this corpus. By making to similarity matrices you can compair the song that is inspired by classical songs and the classicals songs itself. I did this for the songs ‘all by myself’ - Eric Carmen and the song that is it’s source of inspiration ‘Piano Concerto No. 2 in C minor’ - Sergei Rachmaninoff. You can see that the similiarity matrices do correspond and that the patterns look like each other. That looks like they have the same repetitions. ‘All by myself’ is a song in the corpus that has clear influences of Piano Concerto No. 2 in C minor. So that explains why the two self-similarity matrices look like each other.

Some new visualizations: chordograms. Comparison of the inspired newer songs and the classical pieces

chordogram ‘Reverie’ - Ella Fitzgerald

chordogram ‘Rêverie’ - Claude Debussy


chromachrom comparisment

I compaired two song of the corpus using chordograms. The first chordogram is a visualization of ‘My Reverie’ by Ella Fitzgerald. This song contains some clear repetitions. The second chrodogram is a visualization of the clasical song that inspired Ella Fitzgerald, named ‘Rêverie’ by Claude Debussy. An interesting observation is that have some clear similarities. Although Debussy’s Rêverie is bit more stretched out, you can spot the same pattern. This is also something that you can hear back if you listen to the two songs. The lighter/yelllowe parts in the middle and in the end are in both pieces audible. Both the songs sound louder, but in a different way. In Fitzgerald’s song increases sound her voice and in Debussy’s song increases the sound of the instruments.

DTW


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DTW (dynamic timewarping)

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Histogram of tempi

tempo count

tempo density


The tempi of the classical songs vary a lot. It’s almost an evenly distributed graph, only a few more slower songs than faster songs. The different tempi for the inspired newer songs are closer to each other, less distributed. There is a peak for the newer songs around 120 bmp.

Key distribution

graph of key distribution newer songs and classical songs

Track-Level Summaries


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Cepstrograms


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classification

Classification


The overall precision was 71